ORCID Profile
0000-0003-2835-6271
Current Organisations
University of Oxford
,
University of Hertfordshire
,
Oxford Brookes University
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Publisher: Springer Science and Business Media LLC
Date: 12-08-2022
Publisher: BMJ
Date: 18-05-2022
Publisher: Hindawi Limited
Date: 27-01-2022
DOI: 10.1155/2022/1041880
Abstract: With the increasing number and popularity of digital content, the management of digital access rights has become an utmost important field. Through digital rights management systems (DRM-S), access to digital contents can be defined and for this, an efficient and secure authentication scheme is required. The DRM authentication schemes can be used to give access or restrict access to digital content. Very recently in 2020, Yu et al. proposed a symmetric hash and xor-based DRM and termed their system to achieve both security and performance efficiency. Contrarily, in this study, we argue that their scheme has several issues including nonresistance to privileged insider and impersonation attacks. Moreover, it is also to show in this study that their scheme has an incorrect authentication phase and due to this incorrectness, the scheme of Yu et al. lacks user scalability. An improved scheme is then proposed to counter the insecurities and incorrectness of the scheme of Yu et al. We prove the security of the proposed scheme using BAN logic. For a clear picture of the security properties, we also provide a textual discussion on the robustness of the proposed scheme. Moreover, due to the usage of symmetric key-based hash functions, the proposed scheme has a comparable performance efficiency.
Publisher: Hindawi Limited
Date: 2017
DOI: 10.1155/2017/4724852
Abstract: Routing is one of the most important operations in wireless sensor networks (WSNs) as it deals with data delivery to base stations. Routing attacks can cripple it easily and degrade the operation of WSNs significantly. Traditional security mechanisms such as cryptography and authentication alone cannot cope with some of the routing attacks as they come from compromised nodes mostly. Recently, trust mechanism is introduced to enhance security and improve cooperation among nodes. In routing, trust mechanism avoids/includes nodes in routing operation based on the estimated trust value. Many trust-based routing protocols are proposed to secure routing, in which they consider different routing attacks. In this research work, our goal is to explore the current research state and identify open research issues by surveying proposed schemes. To achieve our goal we extensively analyze and discuss proposed schemes based on the proposed framework. Moreover, we evaluate proposed schemes based on two important factors, which are energy consumption and attack resiliency. We discuss and present open research issues in the proposed schemes and research field.
Publisher: Wiley
Date: 18-03-2016
DOI: 10.1111/JAN.12959
Abstract: To identify the practical challenges encountered when using wearable monitors for patients discharged from the intensive care unit. Patients discharged from intensive care units are a high-risk group that might benefit from continuing observation using 'wearable' monitors to enable faster identification of physiological deterioration and facilitate timely clinical action. This area of technological innovation is of key interest to nurses who manage this group of patients. A prospective observational study. An observational study conducted in 2013-2014 used wearable monitors to record continuous observations for patients discharged from an intensive care unit to develop a predictive model of patients likely to deteriorate. Screening data for study eligibility and case report form data to assess monitor tolerance and comfort were collected daily and analysed using Microsoft Access. Patients (n = 2704) were discharged from an intensive care unit during the study, 208 consented to wearing the monitor. Of the 192 included in analysis, 130 (67·7%) removed the monitor before the trial finished. Reasons cited for removal included 'discomfort and irritation' 61 (31·8%) and 'feeling too unwell' 8 (4·2%). Five hundred seventeen patients were screened following adaption of the wearable monitor. Despite design changes, 56 (10·8%) patients were unable to wear monitors for reasons related to their anatomy or condition. Of 124 patients, 65 patients (52·4%) who were approached refused participation. Work is needed to understand wireless monitor comfort and design for acutely unwell patients. Product design needs to develop further, so patients are catered for in flexibility of monitor placement and improved comfort for long-term wear.
Publisher: Springer Science and Business Media LLC
Date: 05-2022
DOI: 10.1038/S41591-022-01772-9
Abstract: A growing number of artificial intelligence (AI)-based clinical decision support systems are showing promising performance in preclinical, in silico evaluation, but few have yet demonstrated real benefit to patient care. Early-stage clinical evaluation is important to assess an AI system's actual clinical performance at small scale, ensure its safety, evaluate the human factors surrounding its use and pave the way to further large-scale trials. However, the reporting of these early studies remains inadequate. The present statement provides a multi-stakeholder, consensus-based reporting guideline for the Developmental and Exploratory Clinical Investigations of DEcision support systems driven by Artificial Intelligence (DECIDE-AI). We conducted a two-round, modified Delphi process to collect and analyze expert opinion on the reporting of early clinical evaluation of AI systems. Experts were recruited from 20 pre-defined stakeholder categories. The final composition and wording of the guideline was determined at a virtual consensus meeting. The checklist and the Explanation & Elaboration (E&E) sections were refined based on feedback from a qualitative evaluation process. In total, 123 experts participated in the first round of Delphi, 138 in the second round, 16 in the consensus meeting and 16 in the qualitative evaluation. The DECIDE-AI reporting guideline comprises 17 AI-specific reporting items (made of 28 subitems) and ten generic reporting items, with an E&E paragraph provided for each. Through consultation and consensus with a range of stakeholders, we developed a guideline comprising key items that should be reported in early-stage clinical studies of AI-based decision support systems in healthcare. By providing an actionable checklist of minimal reporting items, the DECIDE-AI guideline will facilitate the appraisal of these studies and replicability of their findings.
Location: United Kingdom of Great Britain and Northern Ireland
Location: United Kingdom of Great Britain and Northern Ireland
Location: United Kingdom of Great Britain and Northern Ireland
No related grants have been discovered for Sarah Vollam.